GPU-Accelerated Simulation Ensembles of Stochastic Reaction Networks

Köster, Till and Herrmann, Leon and Andelfinger, Philipp and Uhrmacher, Adelinde M. (2022) GPU-Accelerated Simulation Ensembles of Stochastic Reaction Networks. In: Winter Simulation Conference (WSC 2022), 11-14 Dec 2022, Singapore. Proceedings, published by IEEE, pp. 2570-2581.

Full text not available from this repository.
Official URL:


Stochastic Simulation Algorithms are widely used for simulating reaction networks in cellular biology. Due to the stochastic nature of models and the large parameter spaces involved, many simulation runs are frequently needed. We approach the computational challenge by expanding the hardware used for execution by massively parallel graphical-processing-units (GPUs) to execute these ensembles of runs concurrently in a form of coarse-grained parallelization. We employ state-of-the-art algorithms to study the degree to which GPUs can augment the computation resources available for ensemble studies. Furthermore, the challenge of efficient work assignment given the GPU's synchronous mode of execution is explored. There are several algorithmic tradeoffs to consider for models with different execution characteristics, which we investigate in a performance study across four different models. Our results indicate that for some models adding a typical desktop GPU has a similar effect on performance as up to 40 added CPU cores.

Item Type: Conference or Workshop Item (Paper)
Additional Information: DOI: 10.1109/WSC57314.2022.10015448
Projects: ESCeMMo